Skip to main content
SpringerLink
Log in

An adaptive updating protocol for reducing moving object database workload

  • Special Issue Paper
  • Published:
The VLDB Journal Aims and scope Submit manuscript

Abstract

In the last decade, spatio-temporal database research focuses on the design of effective and efficient indexing structures in support of location-based queries such as predictive range queries and nearest neighbor queries. While a variety of indexing techniques have been proposed to accelerate the processing of updates and queries, not much attention has been paid to the updating protocol, which is another important factor affecting the system performance. In this paper, we propose a generic and adaptive updating protocol for moving object databases with less number of updates between objects and the database server, thereby reducing the overall workload of the system. In contrast to the approach adopted by most conventional moving object database systems where the exact locations and velocities last disclosed are used to predict their motions, we propose the concept of Spatio-temporal safe region to approximate possible future locations. Spatio-temporal safe regions provide larger space of tolerance for moving objects, freeing them from location and velocity updates as long as the errors remain predictable in the database. To answer predictive queries accurately, the server is allowed to probe the latest status of objects when their safe regions are inadequate in returning the exact query results. Spatio-temporal safe regions are calculated and optimized by the database server with two contradictory objectives: reducing update workload while guaranteeing query accuracy and efficiency. To achieve this, we propose a cost model that estimates the composition of active and passive updates based on historical motion records and query distribution. More system performance improvements can be obtained by cutting more updates from the clients, when the users of system are comfortable with incomplete but accuracy bounded query results. We have conducted extensive experiments to evaluate our proposal on a variety of popular indexing structures. The results confirm the viability, robustness, accuracy and efficiency of our proposed protocol.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Brinkhoff T.: A framework for generating network-based moving objects. GeoInformatica 6(2), 153–180 (2002)

    Article  MATH  Google Scholar 

  2. Chen S., Jensen C.S., Lin D.: A benchmark for evaluating moving object indexes. PVLDB 1(2), 1574–1585 (2008)

    Google Scholar 

  3. Chen, S., Ooi, B.C., Tan, K.-L., Nascimento, M.A.: St2b-tree: a self-tunable spatio-temporal b+-tree index for moving objects. In: Proceedings of SIGMOD, pp. 29–42 (2008)

  4. Chen S., Ooi B.C., Zhang Z.: An adaptive updating protocol for reducing moving object databases workload. PVLDB 3(1), 735–746 (2010)

    Google Scholar 

  5. Gedik, B., Liu, L.: Mobieyes: distributed processing of continuously moving queries on moving objects in a mobile system. In: Proceedings of EDBT, pp. 67–87 (2004)

  6. Hu, H., Xu, J., Lee, D.L.: A generic framework for monitoring continuous spatial queries over moving objects. In: Proceedings of SIGMOD, pp. 479–490 (2005)

  7. Jensen, C.S., Lin, D., Ooi, B.C.: Query and update efficient B+-tree based indexing of moving objects. In: Proceedings of VLDB, pp. 768–779 (2004)

  8. Lin, D., Jensen, C.S., Ooi, B.C., Saltenis, S.: Efficient indexing of the historical, present, and future positions of moving objects. In: Proceedings of MDM, pp. 59–66 (2005)

  9. Mokbel, M.F., Xiong, X., Aref, W.G.: Sina: Scalable incremental processing of continuous queries in spatio-temporal databases. In: Proceedings of SIGMOD, pp. 623–634 (2004)

  10. Mouratidis, K., Hadjieleftheriou, M., Papadias, D.: Conceptual partitioning: an efficient method for continuous nearest neighbor monitoring. In: Proceedings of SIGMOD, pp. 634–645 (2005)

  11. Ng, V., Kameda, T.: The R-link tree: a recoverable index structure for spatial data. In: Proceedings of DEXA, pp. 163–172 (1994)

  12. Rajagopalan S., Vazirani V.V.: Primal-dual rnc approximation algorithms for set cover and covering integer programs. SIAM J. Comput. 28(2), 525–540 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  13. Saltenis, S., Jensen, C.S., Leutenegger, S.T., Lopez, M.A.: Indexing the positions of continuously moving objects. In: Proceedings of SIGMOD, pp. 331–342 (2000)

  14. Srinivasan, V., Carey, M.J.: Performance of B-tree concurrency control algorithms. In: Proceedings of SIGMOD, pp. 416–425. ACM Press, New York, NY, USA (1991)

  15. Tao, Y., Faloutsos, C., Papadias, D., Liu, B.: Prediction and indexing of moving objects with unknown motion patterns. In: Proceedings of SIGMOD, pp. 611–622 (2004)

  16. Tao, Y., Papadias, D., Sun, J.: The TPR*-tree: an optimized spatio-temporal access method for predictive queries. In: Proceedings of VLDB, pp. 790–801 (2003)

  17. Tao, Y., Papadias, D., Zhai, J., Li, Q.: Venn sampling: a novel prediction technique for moving objects. In: Proceedings of ICDE, pp. 680–691 (2005)

  18. Wolfson O., Sistla A.P., Chamberlain S., Yesha Y.: Updating and querying databases that track mobile units. Distrib. Parallel Databases 7(3), 257–387 (1999)

    Article  Google Scholar 

  19. Wu, W., Guo, W., Tan, K.-L.: Distributed processing of moving k-nearest-neighbor query on moving objects. In: Proceedings of ICDE, pp. 1116–1125 (2007)

  20. Xiong, X., Mokbel, M.F., Aref, W.G.: Sea-cnn: scalable processing of continuous k-nearest neighbor queries in spatio-temporal databases. In: Proceedings of ICDE, pp. 643–654 (2005)

  21. Xiong, X., Mokbel, M.F., Aref W.G.: Lugrid: update-tolerant grid-based indexing for moving objects. In: Proceedings of MDM, p. 13 (2006)

  22. Yiu M.L., Tao Y., Mamoulis N.: The b dual-tree: indexing moving objects by space filling curves in the dual space. VLDB J. 17(3), 379–400 (2008)

    Article  Google Scholar 

  23. Yu, X., Pu, K.Q., Koudas, N.: Monitoring k-nearest neighbor queries over moving objects. In: Proceedings of ICDE, pp. 631–642 (2005)

  24. Zhang, M., Chen, S., Jensen, C.S., Ooi, B.C., Zhang, Z.: Effectively indexing uncertain moving objects for predictive queries. In: Proceedings of VLDB (2009)

  25. Zhang, Z., Cheng, R., Papadias, D., Tung, A.K.H.: Minimizing communication cost for continuos skyline maintenance. In: Proceedings of SIGMOD (2009)

  26. Zhang Z., Yang Y., Tung A.K.H., Papadias D.: Continuous k-means monitoring over moving objects. IEEE Trans. Knowl. Data Eng. 20(9), 1205–1216 (2008)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Computing, National University of Singapore, Singapore, Singapore

    Su Chen & Beng Chin Ooi

  2. Advanced Digital Sciences Center, Illinois at Singapore Pte, Singapore, Singapore

    Zhenjie Zhang

Authors
  1. Su Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Beng Chin Ooi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zhenjie Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Su Chen.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Chen, S., Ooi, B.C. & Zhang, Z. An adaptive updating protocol for reducing moving object database workload. The VLDB Journal 21, 265–286 (2012). https://doi.org/10.1007/s00778-011-0257-3

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00778-011-0257-3

Keywords

Search

Navigation